Chaos in multiplanetary extrasolar systems

TL;DR

This study analyzes the stability of 178 confirmed multiplanetary systems using the MEGNO indicator and machine learning, revealing that most are stable and demonstrating SPOCK's effectiveness in stability assessment.

Contribution

The paper provides a comprehensive stability analysis of confirmed exoplanet systems using MEGNO and compares it with machine learning predictions, highlighting SPOCK's potential as a review tool.

Findings

Approximately 75% of systems are long-term stable.

45 systems exhibit chaotic behavior.

SPOCK effectively predicts system stability.

Abstract

Here we present an initial look at the dynamics and stability of 178 multiplanetary systems which are already confirmed and listed in the NASA Exoplanet Archive. To distinguish between the chaotic and regular nature of a system, the value of the MEGNO indicator for each system was determined. Almost three-quarters of them could be labelled as long-term stable. Only 45 studied systems show chaotic behaviour. We consequently investigated the effects of the number of planets and their parameters on the system stability. A comparison of results obtained using the MEGNO indicator and machine-learning algorithm SPOCK suggests that the SPOCK could be used as an effective tool for reviewing the stability of multiplanetary systems. A similar study was already published by Laskar and Petit in 2017. We compared their analysis based on the AMD criterion with our results. The possible discrepancies are discussed.